Introducing Zonka Feedback MCP Server: Query Your CX Data from Any AI Assistant

A product lead is mid-conversation with Claude, working through a churn problem. She needs to know what detractors said this quarter. So she stops. Opens Zonka Feedback. Finds the project, the theme, the numbers. Copies. Switches back. Pastes.

By then, the thinking has moved on without the data.

The analysis already existed. The path to it was the problem. Today we’re closing that path with the MCP Server. The Zonka Feedback MCP Server puts your CX data inside the AI conversations your team is already having.

What It Costs When CX Data Stays in the Dashboard

We've seen this play out across enough accounts to know it costs you in three places, not one.

a. The "Pull the Numbers" Tax

Before every QBR, every escalation review, every roadmap conversation, someone has to go get the data. Open the platform, run the filters, screenshot or export, paste into the doc or the chat. It takes five minutes. Nobody thinks of it as a problem. But multiply it by every person who needs a CX data point in a meeting they're preparing for, and you're looking at hours of context assembly that adds no insight. Just logistics.

b. The Teams Who Never See It

Your CX team lives in the dashboard. Product doesn't. Leadership doesn't. Customer success checks in when there's an escalation. The people making the biggest decisions about the customer experience are often the ones with the least direct access to what customers are saying. Not because the data isn't available. Because the path to it runs through a tool they don't use daily.

c. The AI That Makes It Up

This one is the least visible and the most dangerous. When your team asks an AI assistant about customer sentiment or NPS trends without a real data source, the model doesn't say "I don't know." It generates an answer. Plausible numbers. Reasonable-sounding themes. Confident analysis. None of it grounded in your actual responses.

That's not a hypothetical risk. It's the default behaviour right now for any team using AI tools without a structured connection to their CX data.

What Your AI Assistant Can Now Query

The Zonka Feedback MCP Server connects your AI assistant to your live CX dataset. MCP stands for Model Context Protocol, an open standard that lets AI tools query external data sources mid-conversation. Instead of your team carrying data out of Zonka Feedback by hand, the AI reaches in and pulls what it needs.

Here's what's queryable.

• CX metrics. NPS, CSAT, CES, and sentiment scores. Your actual numbers from your actual responses. When a product lead asks "what's our NPS this quarter," the answer comes from your data, not from the model's training set.

• AI Intelligence data. The themes, sub-themes, and verbatim customer quotes that your Intelligence Hub already surfaces. A support lead reviewing escalation patterns can pull the exact complaint themes driving volume this month, filtered by urgency or churn risk, without opening a dashboard.

• Operational context. Contacts, segments, locations, data sources. If a CS leader needs detractor feedback from APAC only, or wants to compare sentiment across two survey channels, the filters are built into the query. No export, no pivot table.

• Reputation data. Google Reviews ratings, G2 scores, app store reviews. If you're tracking online reputation inside Zonka Feedback, your AI assistant can pull those numbers alongside your survey data in the same conversation.

Every answer is grounded in your Zonka Feedback dataset. That's the difference between an AI assistant that sounds right and one that actually is.

Trust by Architecture, Not by Policy

There are a few design choices behind the MCP Server that I want to call out because they reflect how we think about opening up your data to external tools.

• Permissions carry over. The roles you've already set inside Zonka Feedback are the roles the MCP Server enforces. If someone can only see data for their location, that's all their AI assistant can query. No separate access layer. No new admin to configure. The governance you've built travels with the data.

• Admin control is explicit. An admin enables MCP access under Settings > AI Features. It's on when you want it on, off when you don't. Not buried three levels deep. Not silently enabled.

• All plans, all regions, one URL. US, EU, India, Australia. Automatic routing, data stays in region. Available on every Zonka Feedback plan. We didn't gate this behind enterprise pricing because the problem it solves isn't an enterprise problem. It's a workflow problem. Every team has it.

The server works with AI assistants like Claude today, with more tools being added. Write capabilities, creating surveys, adding contacts, responding to reviews from inside an AI conversation, are coming next. 

From Intelligence Hub to Every Conversation

If you've been using Zonka Feedback for a while, this is how the pieces connect.

Intelligence Hub does the analysis. It runs thematic analysis across your feedback, classifies experience signals, surfaces sentiment patterns, and tags the verbatim quotes that explain what your scores mean. That's the analytical engine.

Ask AI lets you query that analysis conversationally inside the Zonka Feedback platform. Purpose-built widgets, controlled responses, designed for the person who works inside the product every day.

The MCP Server takes that same intelligence and makes it available outside the platform. Inside Claude. Inside ChatGPT. Inside whichever AI tool your team already has open when the question comes up.

Three layers. One dataset. The only difference is where the question gets asked.

Your Data Should Go Where Your Team Works

The assumption behind every CX platform, ours included, has been that teams will come to the data. Open the dashboard, run the report, read the analysis. And for the people who do that daily, nothing changes. Intelligence Hub, Ask AI, the reporting tools, all of that keeps getting better.

But most of the people who need CX data don't work that way. They work inside an AI assistant, or a doc, or a planning conversation. And if the data doesn't show up there, it doesn't show up at all. It gets replaced by intuition, or by a model confidently making something up.

The MCP Server is built for that reality. Not a better place to look at your data. An open layer that puts your CX intelligence wherever your team already thinks.

That's the direction we're committed to. And it won't stop here.

If your team is already working inside AI assistants and your CX data isn't in those conversations yet, book a demo with us and we'll connect your account and run your first query together.